Large Language Models

NPFL140

The course provides an overview of how large language models work, including theoretical foundations, practical aspects (efficient inference, multilinguality), and the broader context of the models (ethics, philosophy of language). The classes combine classical lecturing with other activities, such as hands-on tutorials or collaborative discussion sessions. To pass the course, students need to work on a group project based on recent shared/competition tasks and take part in a final test.

Prerequisities

Programming in Python, elementary knowledge of neural networks, including basic underlying math (linear algebra, probability, calculus)

Details

EXPLORE THE BLOCKS AND COURSES

STILL SOME QUESTIONS?

Contact us at minor@prg.ai and we will get back to you shortly.

Also, don’t forget to follow us on LinkedIn.